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Fast Calculation of Computer Generated Holograms for 3D Photostimulation through Compressive-Sensing Gerchberg–Saxton Algorithm

Delft Center for Systems and Control, Delft University of Technology, Mekelweg 2, 2628 CD Delft, The Netherlands
Department of Imaging Physics, Delft University of Technology, Lorentzweg 1, 2628 CJ Delft, The Netherlands
Flexible Optical B.V., Polakweg 10-11, 2288 GG Rijswijk, The Netherlands
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
These authors contributed equally to this work.
Methods Protoc. 2019, 2(1), 2;
Received: 29 October 2018 / Revised: 1 December 2018 / Accepted: 18 December 2018 / Published: 20 December 2018
PDF [1087 KB, uploaded 21 December 2018]
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The use of spatial light modulators to project computer generated holograms is a common strategy for optogenetic stimulation of multiple structures of interest within a three-dimensional volume. A common requirement when addressing multiple targets sparsely distributed in three dimensions is the generation of a points cloud, focusing excitation light in multiple diffraction-limited locations throughout the sample. Calculation of this type of holograms is most commonly performed with either the high-speed, low-performance random superposition algorithm, or the low-speed, high performance Gerchberg–Saxton algorithm. This paper presents a variation of the Gerchberg–Saxton algorithm that, by only performing iterations on a subset of the data, according to compressive sensing principles, is rendered significantly faster while maintaining high quality outputs. The algorithm is presented in high-efficiency and high-uniformity variants. All source code for the method implementation is available as Supplementary Materials and as open-source software. The method was tested computationally against existing algorithms, and the results were confirmed experimentally on a custom setup for in-vivo multiphoton optogenetics. The results clearly show that the proposed method can achieve computational speed performances close to the random superposition algorithm, while retaining the high performance of the Gerchberg–Saxton algorithm, with a minimal hologram quality loss. View Full-Text
Keywords: optogenetics; spatial light modulators; computer generated holograms optogenetics; spatial light modulators; computer generated holograms

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Pozzi, P.; Maddalena, L.; Ceffa, N.; Soloviev, O.; Vdovin, G.; Carroll, E.; Verhaegen, M. Fast Calculation of Computer Generated Holograms for 3D Photostimulation through Compressive-Sensing Gerchberg–Saxton Algorithm. Methods Protoc. 2019, 2, 2.

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